upddate example images

app.py

@@ -4,6 +4,15 @@ from ppocr.utils.visual import draw_ser_results
 from PIL import Image
 import gradio as gr
 
+example_dir = './example_images'
+
+example_images = [file for file in os.listdir(example_dir) if file.endswith(('.png', '.jpg', '.jpeg'))]
+
+def load_image(filename):
+    # Construct full file path
+    file_path = os.path.join(example_dir, filename)
+    # Load and return the image
+    return Image.open(file_path)
 
 def inference__ppocr(img_path):
 
@@ -31,7 +40,6 @@ def inference__ppocr(img_path):
 
 
 def inference__ppstructure(img_path):
-
     ppsutructure = PPStructure(
         rec_char_dict_path='zhtw_common_dict.txt',
         use_gpu=False,
@@ -50,10 +58,17 @@ def inference__ppstructure(img_path):
     result = [''.join(f"{element['pred']}:{element['transcription']}") for element in result if element['pred']!='O']
     return image, "\n".join(result)
 
+def update_image_input(filename):
+    # Construct full file path
+    file_path = os.path.join(example_dir, filename)
+    # Return the file path
+    return file_path
+
+
 with gr.Blocks() as demo:    
     gr.Markdown("<p style='text-align: center; font-size: 50px; font-weight: bold;'>Form Understanding Project - Certificate of Diagnosis</p>")
     gr.Markdown("Support languages: Traditional Chinese 🇹🇼")
-    gr.Markdown("version：0.1")
+    gr.Markdown("version:0.1")
     gr.Markdown("""
     ## Usage Description
     This interface is designed to process and extract information from Certificates of Diagnosis. 
@@ -62,16 +77,26 @@ with gr.Blocks() as demo:
     3. Click 'Process' to extract information from the uploaded certificate.
     4. The processed image and extracted text will be displayed on the right.
     """)
+
     with gr.Row():
         with gr.Column():
             gr.Markdown("#### Input Image")
             image_input = gr.Image(type='filepath', label='Upload Image')
+            # example_dropdown = gr.Dropdown(label="Choose an example", choices=example_images)
+            image_selection = gr.Radio(label="Select an Example Image", choices=example_images)
+
             submit_btn  = gr.Button("Process")
         with gr.Column():
             gr.Markdown("#### Processed Image")
             image_output = gr.Image(type="pil", label="Processed Image")
             gr.Markdown("#### Extracted Text")
             text_output  = gr.Textbox(label="Extracted Text")
+    
+    image_selection.change(
+        update_image_input,
+        inputs=[image_selection],
+        outputs=[image_input]
+    )
 
     submit_btn.click(
         inference__ppstructure,